This paper aims to simulate the nanofluid forced convection in a microchannel. According to the results, at high Reynolds numbers and higher nanofluid volume fractions, an increase in the rib height and slip coefficient further improved the heat transfer rate. The ribs also affect the flow physics depending on the Reynolds number so that the slip velocity decreases with increasing the nanofluid volume fraction and rib height.
Forced heat transfer of the water–copper nanofluid is numerically studied in a two dimensional microchannel. The effects of the slip coefficient, Reynolds number, nanofluid volume fraction and rib height are investigated on the average Nusselt number, slip velocity on the microchannel wall and the performance evaluation criterion.
In contrast, the slip velocity increases with increasing the Reynolds number and slip coefficient. Afterwards, a non-parametric function estimation is performed relying on the artificial neural network.
Finally, the Genetic Algorithm was used to establish a set of optimal decision parameters for the problem
